Comparison of control strategies for hysteresis attenuation in electromechanical actuators subject to dispersion
Abstract
This paper addresses the difficulties of designing highly efficient robust controllers for a class of systems
exhibiting high hysteresis with parameters dispersion that limits control accuracy and performance homogene-
ity over the parametric uncertainties range. Two control strategies to solve the problem are assessed. First,
a Reference Model Sliding Mode Control (RMSMC) feedback controller known to be robust to parametric
uncertainty is designed to compensate for hysteresis, regardless of the hysteresis quantity. Secondly, a strategy
based on a feedforward controller with a Neural Network inverse model and a PID feedback controller is
proposed. In this case, hysteresis dispersion is addressed by integrating a backlash estimator for
computing the Neural Network inverse model. The control strategies are implemented for position control of
a Limited-Angle Torque Motor (LATM) exhibiting uncertain hysteresis. Experimental tests demonstrated the
very good accuracy and robustness of the Neural Network inverse model and the PID controller for position
tracking when the LATM is subject to dispersion and the benefits of the Reference Model Sliding Mode Control
(RMSMC) feedback controller for the rejection of external disturbances.
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